Search Results (550)

Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO₂ emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents a promising avenue to improve the sustainability, reliability, and efficiency of urban transport networks. A storage system is needed to both ensure a continuous power supply and meet train demand at the station. Batteries (BTs) offer high energy density, while supercapacitors (SCs) offer both a large number of charge and discharge cycles, and high-power density. This paper proposes a hybrid RES (photovoltaic and wind), combined with batteries and supercapacitors constituting the hybrid energy storage system (HESS). One major drawback of trains is the long charging time required in stations, so they have been fitted with SCs to allow them to charge up quickly. A new fuzzy energy management strategy (F-EMS) is proposed. This supervision strategy optimizes the power flow between renewable energy sources, HESS, and trains. DC bus voltage regulation is involved, maintaining BT and SC charging levels within acceptable ranges. The simulation results, carried out using MATLAB/Simulink, demonstrate the effectiveness of the suggested fuzzy energy management strategy for various production conditions and train demand. Full article

Residents’ attitudes towards offshore wind farms have been researched extensively over the past few decades. In this research, the precept that offshore wind farms influence residents’ well-being is implicit. Only a few studies have directly examined residents’ knowledge, perceived benefits, and acceptance. This study attempts to go beyond attitude-based research and explicitly examines factors influencing acceptance decision-making. The data for this qualitative study was collected through face-to-face interviews at a proposed offshore wind farm site in Perth, Western Australia. Results from the study suggest that offshore wind farms are not perceived or responded to uniformly by residents. This study provides a more comprehensive understanding of the dynamics and complexities behind identifying and explaining how residents of designated communities perceive offshore wind farms in a nuanced manner. Therefore, this study proffers significant theoretical discussions and practical implications regarding developing sustainable renewable energy alternatives in cities across Australia. Full article

The increasing penetration of renewable energy sources (RESs), particularly solar photovoltaic (PV) sources, has introduced significant uncertainty into power system operations, challenging traditional scheduling models and threatening system reliability. This study proposes a Fuzzy Unit Commitment Model (FUCM) designed to address uncertainty in load demand, solar PV generation, and spinning reserve requirements by applying fuzzy linear programming techniques. The FUCM reformulates uncertain constraints using triangular membership functions and integrates them into a mixed-integer linear programming (MILP) framework. The model’s effectiveness is demonstrated through two case studies: a 30-generator test system and a national-scale power system in Thailand comprising 171 generators across five service zones. Simulation results indicate that the FUCM consistently produces stable scheduling solutions that fall within deterministic upper and lower bounds. The model improves reliability metrics, including reduced loss-of-load probability and minimized load deficiency, while maintaining acceptable computational performance. These results suggest that the proposed approach offers a practical and scalable method for unit commitment planning under uncertainty. By enhancing both operational stability and economic efficiency, the FUCM contributes to the sustainable management of RES-integrated power systems. Full article

The production of thermal energy in buildings using internal greenhouses makes it possible to obtain substantial gains in energy consumption and, at the same time, contribute to improving occupants’ thermal comfort (TC) levels. This article proposes a study on the producing and transporting of renewable thermal energy in a circular auditorium equipped with an enveloping semi-circular greenhouse. The numerical study is based on software that simulates the building geometry and the building thermal response (BTR) numerical model and assesses the TC level and indoor air quality (IAQ) provided to occupants in spaces ventilated by the proposed system. The building considered in this study is a circular auditorium constructed from three semi-circular auditoriums supplied with internal semi-circular greenhouses. Each of the semi-circular auditoriums faces south, northeast, and northwest, respectively. The semi-circular auditoriums are occupied by 80 people each: the one facing south throughout the day, while the one facing northeast is only occupied in the morning, and the one facing northwest is only occupied in the afternoon. The south-facing semi-circular greenhouse is used by itself to heat all three semi-circular auditoriums. The other two semi-circular greenhouses are only used to heat the interior space of the greenhouse. It was considered that the building is located in a Mediterranean-type climate and subject to the typical characteristics of clear winter days. The results allow us to verify that the proposed heating system, in which the heat provided to the occupied spaces is generated only in the semi-circular greenhouse facing south, can guarantee acceptable TC conditions for the occupants throughout the occupancy cycle. Full article

As the demand for energy-efficient homes continues to rise, the importance of advanced mechanical ventilation systems in maintaining indoor air quality (IAQ) has become increasingly evident. However, challenges related to energy balance, IAQ, and occupant thermal comfort persist. This review examines the performance of mechanical ventilation systems in regulating indoor climate, improving air quality, and minimising energy consumption. The findings indicate that demand-controlled ventilation (DCV) can enhance energy efficiency by up to 88% while maintaining CO₂ concentrations below 1000 ppm during 76% of the occupancy period. Heat recovery systems achieve efficiencies of nearly 90%, leading to a reduction in heating energy consumption by approximately 19%. Studies also show that employing mechanical rather than natural ventilation in schools lowers CO₂ levels by 20–30%. Nevertheless, occupant misuse or poorly designed systems can result in CO₂ concentrations exceeding 1600 ppm in residential environments. Hybrid ventilation systems have demonstrated improved thermal comfort, with predicted mean vote (PMV) values ranging from –0.41 to 0.37 when radiant heating is utilized. Despite ongoing technological advancements, issues such as system durability, user acceptance, and adaptability across climate zones remain. Smart, personalized ventilation strategies supported by modern control algorithms and continuous monitoring are essential for the development of resilient and health-promoting buildings. Future research should prioritize the integration of renewable energy sources and adaptive ventilation controls to further optimise system performance. Full article

Renewable energy projects are critical for sustainable development, yet their success often hinges on local community acceptance. This study refines the Community Acceptance Framework to classify and better understand the social and behavioral factors that shape community responses to renewable energy projects. To support the reclassification, we draw selectively on three psychological concepts to refine definition and streamline categories. Based on a systematic review of 212 studies, we identified 29 influencing factors and categorized them into a seven-dimensional framework: social, economic, environmental, political, process, project details, and temporal. The findings reveal that financial capital, which reflects economic gains, emerges as the most frequently cited factor influencing local acceptance. However, when viewed dimensionally, the social dimension encompassing factors such as social capital, cognitive response, and cultural capital accounts for the largest share of influencing factors. Additionally, the often-overlooked political and temporal dimensions highlight the importance of governance quality and timely community engagement. While the framework offers a more robust and context-sensitive tool for analyzing acceptance dynamics, empirical validation is needed to assess its practical applicability. Nevertheless, the refined CAF can guide policymakers, researchers, and practitioners in designing renewable energy initiatives that are both technically sound, economically viable, and socially inclusive. Full article

This study investigates the influence of monthly income level (low, medium, and high) on consumer behavior regarding a newly launched cream cheese product enriched with berry by-products. A panel of 345 participants was surveyed, and data were analyzed using the Kruskal–Wallis and Mann–Whitney tests. Most consumers were environmentally aware, recognizing the impact of personal food waste and expressing support for food products incorporating by-products. Respondents also favored the use of renewable energy and reducing greenhouse gas emissions in the food industry. Higher income levels were associated with greater health awareness and increased acceptance of cream cheese with berry by-products, with the high-income group showing a greater willingness to pay a premium. Health benefits and the product’s natural character were the main advantages identified. Individuals with lower incomes were more open to trying unfamiliar foods when ingredient details were not provided, while higher-income respondents expressed greater hesitation and distrust toward new products. Willingness to try novel items decreased with income level. Statistically significant differences (p < 0.05) were found between income groups for label reading, support for mountain dairies, and the influence of product origin, health benefits, nutrient diversity, pricing concerns, and consumer confidence in purchasing cream cheese with berry by-products. These findings are important for understanding how income affects consumer perceptions and willingness to consume innovative, sustainable food products like berry-enriched cream cheese, highlighting key areas for targeted marketing and product development. Full article

Power-to-X (ptx) technologies are considered a promising solution for enabling the storage and sectoral integration of renewable energy, playing a vital role in the sustainable transition of industrialized energy systems. This study investigates the public acceptance of ptx technologies in Germany using a quantitative, environmental–psychological framework. Key influencing factors such as social and personal norms, environmental awareness, and openness to innovation are analyzed. A particular focus is placed on generational differences, comparing the perceptions of youth (16–25 years) and adults (>25 years) through a representative online survey. The results reveal a general lack of knowledge about ptx technologies yet a positive assessment of their decarbonization potential. Ecological impact—particularly the ability to reduce CO₂ emissions—emerges as the strongest predictor of acceptance. This is closely tied to conditions such as the use of renewable electricity and sustainable sourcing of carbon and water. Notably, acceptance among youth is also influenced by environmental awareness, prior knowledge, and perceived behavioral control. The results show that, in general, there is still a need for improved science communication to address the existing uncertainties in the population. At the same time, age-specific approaches are required, as perceptions and acceptance factors differ significantly between younger and older age groups. Full article

The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in 2023 (33% market share), faces infrastructure gaps constraining further growth. China is strategically mitigating CO₂ emissions while fostering economic expansion, notwithstanding constraints such as suboptimal battery technology advancements, elevated production expenditure, and enduring ecological impacts. This Political, Economic, Social, Technological, Legal, Environmental (PESTLE) assessment, operationalized through a survey of 800 stakeholders and Statistical Package for the Social Sciences IBM SPSS SPSS (Version 28) quantitative analysis (factor loading = 0.73 for Technology; eigenvalue = 4.12), identifies infrastructure gaps as the dominant barrier (72% of stakeholders). Political factors (β = 0.82) emerged as the strongest adoption predictor, outweighing economic subsidies in significance. The adoption of EVs in China presents a significant prospect for reducing CO₂ emissions and advancing technology. However, economic barriers, market dynamics, inadequate infrastructure, regulatory uncertainty, and social acceptance issues are addressed in the assessment. The study recommends prioritizing infrastructure investment (e.g., 500 K fast-charging stations by 2027) and policy stability to overcome adoption barriers. This study provides three key advances: (1) quantification of PESTLE factor weights via factor analysis, revealing technological (infrastructure) and political factors as dominant; (2) identification of infrastructure gaps, not subsidies, as the primary adoption barrier; and (3) demonstration of infrastructure’s persistence post-subsidy cuts. These insights redefine EV adoption priorities in China. Full article

Alternative fuels obtained from renewable sources, providing low greenhouse gas emissions and high energy efficiency, offer significant advantages in terms of sustainability. In addition, the wide applicability of these fuel types in sectors such as housing, transportation, and industry creates significant opportunities in terms of reducing dependence on fossil fuels. Alternative fuels should be evaluated not only according to their environmental contributions but also based on multi-dimensional criteria such as economic cost, technical suitability, sustainability level, fuel properties, infrastructure requirements, and social acceptance. In this context, a comparative analysis of alternative fuel types in terms of various basic parameters is no longer optional, but a necessity. These parameters generally include symmetrical relationships such as balanced trade-offs between economic and environmental dimensions or mutual effects between technical and social criteria. However, they also show variability and uncertainty depending on the fuel type. Therefore, Spherical Fuzzy Multi-Criteria Decision Making (SF-MCDM) methods, which can effectively represent symmetry in membership and hesitation degrees, have been used to achieve more realistic and reliable results in uncertain decision environments. The proposed model provides a systematic and flexible evaluation structure that helps decision makers determine the most appropriate alternative fuel options and contributes to the formation of sustainable energy policies. Full article

In the current context, where environmental concerns are gaining increased attention, the transition toward sustainable urban mobility stands out as a necessary and responsible step. Technological advancements over the past decade have brought private autonomous vehicles, particularly those defined by the Society of Automotive Engineers Levels 4 and 5, into focus as promising solutions for mitigating road congestion and reducing greenhouse gas emissions. However, the extent to which Autonomous Vehicles can fulfill this potential depends largely on user acceptance, patterns of use, and their integration within broader green energy and sustainability policies. The present paper aims to develop an integrated conceptual model that links behavioral determinants to environmental outcomes, assessing how individuals’ intention to adopt private autonomous vehicles can contribute to sustainable urban mobility. The model integrates five psychosocial determinants—perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control—with contextual variables such as energy source, infrastructure availability, and public policy. These components interact to predict users’ intention to adopt AVs and their perceived contribution to urban sustainability. Methodologically, the study builds on a narrative synthesis of the literature and proposes a framework applicable to empirical validation through structural equation modeling (SEM). The model draws on established frameworks such as Technology Acceptance Model (TAM), Theory of Planned Behavior, and Unified Theory of Acceptance and Use of Technology, incorporating constructs including perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control, constructs later to be examined in relation to key contextual variables, including the energy source powering Autonomous Vehicles—such as electricity from mixed or renewable grids, hydrogen, or hybrid systems—and the broader policy environment (regulatory frameworks, infrastructure investment, fiscal incentives, and alignment with climate and mobility strategies and others). The research provides relevant directions for public policy and behavioral interventions in support of the development of clean and smart urban transport in the age of automation. Full article

The use of geothermal energy is gaining strategic importance in the context of sustainable development and the decarbonisation of local energy systems. As a stable and low-emission renewable energy source, geothermal energy offers tangible environmental and social benefits, including improved air quality, reduced greenhouse gas emissions, and enhanced energy independence. This article presents a comprehensive overview of the social dimensions of geothermal energy deployment in Poland, with a particular focus on environmental impacts, public acceptance, and participatory governance. Based on a Polish geothermal district heating system example, the paper demonstrates that geothermal projects can significantly reduce local pollution and support low-carbon economic transitions. The study includes a comparative assessment of avoided emissions, a critical discussion of potential social barriers, and SWOT and PESTEL analyses identifying systemic enablers and constraints. The authors argue that for geothermal energy to fulfil its sustainability potential, it must be supported by inclusive planning, transparent communication, and a holistic policy framework integrating environmental, technological, and social criteria. Full article

This study investigates the social and economic dimensions of Greece’s energy transition, focusing on the distinct contexts of mainland Western Macedonia and Insular Greece. Utilizing social innovation tools, including the Stakeholder Persona and the Iceberg Model, the research reveals significant regional variations in stakeholder concerns, priorities, and awareness levels regarding energy transition issues. Findings indicate that while Insular Greece prioritizes energy security and public acceptance of renewable energy solutions, mainland Greece emphasizes job security and economic diversification. The study highlights the necessity for tailored energy transition strategies that address local needs and foster community engagement. Furthermore, it underscores the importance of enhancing awareness and understanding of methodologies such as Life Cycle Assessment and Life Cycle Cost Analysis to empower stakeholders in making informed decisions. Integrating insights from various layers of the Iceberg Model, this research provides a framework for developing innovative technologies and policies that support a fair and sustainable energy transition in Greece, ensuring that no community is left behind in the global shift towards sustainability. This comprehensive approach seeks to mitigate environmental impacts but also to create economic opportunities that align with each community’s social and cultural fabric. Full article

The review provides the results of the analysis of research publications in the field of energy economy on a global scale. The review aims to test three hypotheses and build and analyze the main trend lines and clusters to determine the direction of movement of new knowledge in the energy economy research. This review delves into the multifaceted nature of energy transitions, highlighting the pivotal role of policy frameworks, financial instruments, and technological innovation. By examining the socio-economic implications of renewable energy deployment and addressing the challenges associated with energy storage and grid integration, this study contributes to the ongoing discourse on sustainable energy development. The review used scientometric, correlation, and bibliometric methods of analysis. Artificial Intelligence was used to process 411,396 units of information (a special prompt was created). There is a new scientific result: (a) research hypotheses 1 and 3 were accepted, research Hypothesis 2 was rejected; (b) new trend lines showed the directions where the global energy economy is heading; (c) new clusters showed the top five leading countries and top 10 keywords in the field of energy economy; (d) leading journals in the studied area were found. The review indicated an underrepresentation of specialized journals in this field among the top journals. The review also showed that several keywords characterizing the sixth technological paradigm are missing from the top 10 keywords. This result suggests that these research areas were underrepresented in citation-based bibliometric data in energy in 2021–2024. The review is useful to identify promising and problematic areas for future research in the global energy economy. Full article

Urban morphology critically shapes environmental performance, yet few studies integrate multiple sustainability targets within a unified modeling framework for its design optimization. This study proposes a data-driven, multi-scale approach that combines parametric simulation, artificial neural network-based multi-task learning (MTL), SHAP interpretability, and NSGA-II optimization to assess and optimize urban form across 18 districts in Hong Kong. Four key sustainability targets—photovoltaic generation (PVG), accumulated urban heat island intensity (AUHII), indoor overheating degree (IOD), and carbon emission intensity (CEI)—were jointly predicted using an artificial neural network-based MTL model. The prediction results outperform single-task models, achieving R² values of 0.710 (PVG), 0.559 (AUHII), 0.819 (IOD), and 0.405 (CEI), respectively. SHAP analysis identifies building height, density, and orientation as the most important design factors, revealing trade-offs between solar access, thermal stress, and emissions. Urban form design strategies are informed by the multi-objective optimization, with the optimal solution featuring a building height of 72.11 m, building centroid distance of 109.92 m, and east-facing orientation (183°). The optimal configuration yields the highest PVG (55.26 kWh/m²), lowest CEI (359.76 kg/m²/y), and relatively acceptable AUHII (294.13 °C·y) and IOD (92.74 °C·h). This study offers a balanced path toward carbon reduction, thermal resilience, and renewable energy utilization in compact cities for either new town planning or existing district renovation. Full article